A composite semiparametric homogeneity test for the distributions of multigroup interval-bounded longitudinal data.

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Zhanfeng Wang, Wenmei Li, Hao Ding, Dongsheng Tu
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引用次数: 0

Abstract

Motivated by comparing the distribution of longitudinal quality of life (QoL) data among different treatment groups from a cancer clinical trial, we propose a semiparametric test statistic for the homogeneity of the distributions of multigroup longitudinal measurements, which are bounded in a closed interval with excess observations taking the boundary values. Our procedure is based on a three-component mixed density ratio model and a composite empirical likelihood for the longitudinal data taking values inside the interval. A nonparametric bootstrap method is applied to calculate the p-value of the proposed test. Simulation studies are conducted to evaluate the proposed procedure, which show that the proposed test is effective in controlling type I errors and more powerful than the procedure which ignores the values on the boundaries. It is also robust to the model mispecification than the parametric test. The proposed procedure is also applied to compare the distributions of the scores of Physical Function subscale and Global Heath Status between the patients randomized to two treatment groups in a cancer clinical trial.

多组区间有界纵向数据分布的复合半参数齐性检验。
通过比较癌症临床试验中不同治疗组的纵向生活质量(QoL)数据分布,我们提出了一种半参数检验统计量,用于多组纵向测量分布的均匀性,这些分布在一个封闭的区间内,过量的观察值取边界值。我们的程序基于三组分混合密度比模型和纵向数据在区间内取值的复合经验似然。采用非参数自举法计算所提出检验的p值。仿真结果表明,该方法能有效地控制第一类误差,且比忽略边界值的方法更有效。与参数检验相比,该方法对模型错定性具有较强的鲁棒性。所提出的程序也被用于比较在癌症临床试验中随机分配到两个治疗组的患者的身体功能亚量表和整体健康状况的分数分布。
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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
期刊介绍: The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers: Drug, device, and biological research and development; Drug screening and drug design; Assessment of pharmacological activity; Pharmaceutical formulation and scale-up; Preclinical safety assessment; Bioavailability, bioequivalence, and pharmacokinetics; Phase, I, II, and III clinical development including complex innovative designs; Premarket approval assessment of clinical safety; Postmarketing surveillance; Big data and artificial intelligence and applications.
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